A reverse order life cycle approach to enhance systems engineering education at undergraduate level

Abstract: The advances of Industry 4.0 lead the transition into the era of complex systems, requiring systems solutions for complex problems, increasing the interest in the development of systems engineers. However, traditional systems thinking may lose its effectiveness in this new context, which leads to a challenge in systems engineering education. This research aims to better prepare systems engineers of the future by addressing the disconnect which exist between systems engineering education at undergraduate level, and the real-life complex systems seen in society today though the implementation of a reverse order life cycle approach. By following the reverse order life cycle approach with a familiar electrical appliance, such as the electric kettle, in the classroom, undergraduate systems engineering students were able to gain the necessary insight and understanding regarding the dynamics of complex systems the underlying systems engineering concepts

A reverse order life cycle approach to enhance systems engineering education at undergraduate level

The advances of Industry 4.0 lead the transition into the era of complex systems, requiring systems solutions for complex problems, increasing the interest in the development of systems engineers. However, traditional systems thinking may lose its effectiveness in this new context, which leads to a challenge in systems engineering education. This research aims to better prepare systems engineers of the future by addressing the disconnect which exist between systems engineering education at undergraduate level, and the real-life complex systems seen in society today though the implementation of a reverse order life cycle approach. By following the reverse order life cycle approach with a familiar electrical appliance, such as the electric kettle, in the classroom, undergraduate systems engineering students were able to gain the necessary insight and understanding regarding the dynamics of complex systems the underlying systems engineering concepts.Institute for Science and Technology Education (ISTE

Using agent based simulation to empirically examine complexity in carbon footprint business process

Through the critical analysis of the extant literature, it is observed that Simulation is widely used as a research method in Natural Sciences, Engineering and Social Sciences, in addition to argumentation and formalisation as the third way of carrying out research. Simulation is not so widely used in Business and Management research as it ought to have been, though this is changing for the better with the technological advances in computers and their computational power. These technological advances enhance the capability of theoretical research models, in defining a problem and their use in empirically examining a solution to the problem in simulated reality, like never before. Management journal searches for “Simulation and Complexity Theory” returned nil or zero returns, which explain that this combination is not popular in management research, though they are used individually more often. The major objective of this paper is to analyse some of the conceptual (or theoretical) and methodological (or empirical) contributions that Agent Based Simulation and Complexity Theory can make to the business and management community in their business process related research In view of this, some basic ideas are discussed of using Agent Based Simulation as a method in Business and Management Studies research and how an Agent Based Model can be applied to a business process as complex as Carbon Footprint. It is in this context that the use of Complexity as the base theory to empirically examine a business process is discussed. Throughout this article, our research on complex adaptive systems (e.g., Accounting Information System) in continuously changing organisations managing complex business processes (e.g., Carbon Footprint business process) is considered as the basis for illustrating some of the concepts. Through this article, avenues for further management research using these tools and methodology are suggested

EXPLOITING KASPAROV'S LAW: ENHANCED INFORMATION SYSTEMS INTEGRATION IN DOD SIMULATION-BASED TRAINING ENVIRONMENTS

Despite recent advances in the representation of logistics considerations in DOD staff training and wargaming simulations, logistics information systems (IS) remain underrepresented. Unlike many command and control (C2) systems, which can be integrated with simulations through common protocols (e.g., OTH-Gold), many logistics ISs require manpower-intensive human-in-the-loop (HitL) processes for simulation-IS (sim-IS) integration. Where automated sim-IS integration has been achieved, it often does not simulate important sociotechnical system (STS) dynamics, such as information latency and human error, presenting decision-makers with an unrealistic representation of logistics C2 capabilities in context. This research seeks to overcome the limitations of conventional sim-IS interoperability approaches by developing and validating a new approach for sim-IS information exchange through robotic process automation (RPA). RPA software supports the automation of IS information exchange through ISs’ existing graphical user interfaces. This “outside-in” approach to IS integration mitigates the need for engineering changes in ISs (or simulations) for automated information exchange. In addition to validating the potential for an RPA-based approach to sim-IS integration, this research presents recommendations for a Distributed Simulation Engineering and Execution Process (DSEEP) overlay to guide the engineering and execution of sim-IS environments.Major, United States Marine CorpsApproved for public release. Distribution is unlimited

Hypocrea jecorina CEL6A protein engineering

The complex technology of converting lignocellulose to fuels such as ethanol has advanced rapidly over the past few years, and enzymes are a critical component of this technology. The production of effective enzyme systems at cost structures that facilitate commercial processes has been the focus of research for many years. Towards this end, the H. jecorina cellobiohydrolases, CEL7A and CEL6A, have been the subject of protein engineering at Genencor. Our first rounds of cellobiohydrolase engineering were directed towards improving the thermostability of both of these enzymes and produced variants of CEL7A and CEL6A with apparent melting temperatures above 70°C, placing their stability on par with that of H. jecorina CEL5A (EG2) and CEL3A (BGL1). We have now moved towards improving CEL6A- and CEL7A-specific performance in the context of a complete enzyme system under industrially relevant conditions. Achievement of these goals required development of new screening strategies and tools. We discuss these advances along with some results, focusing mainly on engineering of CEL6A

Live Biofeedback as a User Interface Design Element: A Review of the Literature

With the advances in sensor technology and real-time processing of neurophysiological data, a growing body of academic literature has begun to explore how live biofeedback can be integrated into information systems for everyday use. While researchers have traditionally studied live biofeedback in the clinical domain, the proliferation of affordable mobile sensor technology enables researchers and practitioners to consider live biofeedback as a user interface element in contexts such as decision support, education, and gaming. In order to establish the current state of research on live biofeedback, we conducted a literature review on studies that examine self and foreign live biofeedback based on neurophysiological data for healthy subjects in an information systems context. By integrating a body of highly fragmented work from computer science, engineering and technology, information systems, medical science, and psychology, this paper synthesizes results from existing research, identifies knowledge gaps, and suggests directions for future research. In this vein, this review can serve as a reference guide for researchers and practitioners on how to integrate self and foreign live biofeedback into information systems for everyday use

A review on analysis and synthesis of nonlinear stochastic systems with randomly occurring incomplete information

Copyright q 2012 Hongli Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modeling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly occurring uncertainties, randomly occurring nonlinearities, randomly occurring saturation, randomly missing measurements and randomly occurring quantization. Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system. In this paper, we aim to survey some recent advances on the analysis and synthesis problems for nonlinear stochastic systems with randomly occurring incomplete information. The developments of the filtering, control and fault detection problems are systematically reviewed. Latest results on analysis and synthesis of nonlinear stochastic systems are discussed in great detail. In addition, various distributed filtering technologies over sensor networks are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out. © 2012 Hongli Dong et al.This work was supported in part by the National Natural Science Foundation of China under Grants 61273156, 61134009, 61273201, 61021002, and 61004067, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Science Foundation of the USA under Grant No. HRD-1137732, and the Alexander von Humboldt Foundation of German

Collaborative perception architecture in smart cities

Autonomous Driving Systems have become a reality in our society. Everyday, progress is made to increase vehicles' autonomy to drive without restrictions in roads and cities. To achieve that, researchers are always seeking for new methods to ensure the safety of the vehicles. A promising strategy is to improve the quality of the collected perception data as it directly influences the overall performance of the autonomous system. However, despite the advances achieved in detection methods and algorithms, perception is currently physically restricted by the available on-board sensors and their line-of-sight. To overcome this limitation, the autonomous system should not only capture on-board perception data, but also enhance it with data exchanged with other agents in the environment. This is known in research as Collaborative Perception, where mobile and stationary agents share object detection and sensor data inside an Intelligent Transport Systems network. This master's thesis brings together a collection of ETSI standards with the goal of developing a well-defined architecture for future implementation of a Secure Collaborative Perception Network in the context of Smart Cities. The architecture has been designed using the open-source software Capella Arcadia following a Model Based Software Engineering methodology